大数据,大问题?如何规避生物多样性绘图中的问题并确保取得有意义的结果

IF 5.4 1区 环境科学与生态学 Q1 BIODIVERSITY CONSERVATION
Ecography Pub Date : 2024-05-30 DOI:10.1111/ecog.07115
Alice C. Hughes, James B. Dorey, Silas Bossert, Huijie Qiao, Michael C. Orr
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引用次数: 0

摘要

我们对生物多样性的了解取决于充足的数据、可靠的方法和现实的模型。没有对物种分布的准确评估,我们就无法有效地确定目标并阻止生物多样性的丧失。物种分布图是这些工作的基础,但无数的研究都没有考虑到可靠的物种分布图绘制实践中最基本的假设,从而损害了其结果的可信度,并可能误导和阻碍保护和管理工作。在此,我们利用近期文献和更广泛的保护社区中的实例来强调当前实践中的重大缺陷及其对分析和保护管理的影响。我们详细介绍了不同的数据过滤决定如何影响分析结果,并为更可靠的分析提供了实用的建议和步骤,同时也了解了现有数据可靠允许的范围以及最合适的方法。虽然由于数据有限和存在偏差,许多分类群不可能进行完美的分析,但确保我们在合理的范围内使用数据并了解固有的假设对于确保适当使用数据至关重要。通过接受和实施这些最佳实践,我们可以确保生物多样性分析的准确性并提高其可比性,最终提高我们使用数据的能力,促进我们对自然世界的保护。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Big data, big problems? How to circumvent problems in biodiversity mapping and ensure meaningful results

Big data, big problems? How to circumvent problems in biodiversity mapping and ensure meaningful results

Our knowledge of biodiversity hinges on sufficient data, reliable methods, and realistic models. Without an accurate assessment of species distributions, we cannot effectively target and stem biodiversity loss. Species range maps are the foundation of such efforts, but countless studies have failed to account for the most basic assumptions of reliable species mapping practices, undermining the credibility of their results and potentially misleading and hindering conservation and management efforts. Here, we use examples from the recent literature and broader conservation community to highlight the substantial shortfalls in current practices and their consequences for both analyses and conservation management. We detail how different decisions on data filtering impact the outcomes of analysis and provide practical recommendations and steps for more reliable analysis, whilst understanding the limits of what available data will reliably allow and what methods are most appropriate. Whilst perfect analyses are not possible for many taxa given limited data, and biases, ensuring we use data within reasonable limits and understanding inherent assumptions is crucial to ensure appropriate use. By embracing and enacting such best practices, we can ensure both the accuracy and improved comparability of biodiversity analyses going forward, ultimately enhancing our ability to use data to facilitate our protection of the natural world.

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来源期刊
Ecography
Ecography 环境科学-生态学
CiteScore
11.60
自引率
3.40%
发文量
122
审稿时长
8-16 weeks
期刊介绍: ECOGRAPHY publishes exciting, novel, and important articles that significantly advance understanding of ecological or biodiversity patterns in space or time. Papers focusing on conservation or restoration are welcomed, provided they are anchored in ecological theory and convey a general message that goes beyond a single case study. We encourage papers that seek advancing the field through the development and testing of theory or methodology, or by proposing new tools for analysis or interpretation of ecological phenomena. Manuscripts are expected to address general principles in ecology, though they may do so using a specific model system if they adequately frame the problem relative to a generalized ecological question or problem. Purely descriptive papers are considered only if breaking new ground and/or describing patterns seldom explored. Studies focused on a single species or single location are generally discouraged unless they make a significant contribution to advancing general theory or understanding of biodiversity patterns and processes. Manuscripts merely confirming or marginally extending results of previous work are unlikely to be considered in Ecography. Papers are judged by virtue of their originality, appeal to general interest, and their contribution to new developments in studies of spatial and temporal ecological patterns. There are no biases with regard to taxon, biome, or biogeographical area.
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